DOI: 10.1111/gcb.12598
论文题名: Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts
作者: Crase B. ; Liedloff A. ; Vesk P.A. ; Fukuda Y. ; Wintle B.A.
刊名: Global Change Biology
ISSN: 13541013
出版年: 2014
卷: 20, 期: 8 起始页码: 2566
结束页码: 2579
语种: 英语
英文关键词: Boosted regression tree models
; Climate change
; Generalized boosting models
; Mangrove
; Niche model
; Sea level rise
; Spatial autocorrelation
; Species distribution model
Scopus关键词: accuracy assessment
; autocorrelation
; climate change
; climate effect
; community response
; forecasting method
; niche
; parameterization
; regression analysis
; spatial distribution
; rain
; Australia
; climate change
; forecasting
; Lythraceae
; Rhizophoraceae
; spatial analysis
; theoretical model
; Australia
; Climate Change
; Forecasting
; Lythraceae
; Models, Theoretical
; Rain
; Rhizophoraceae
; Spatial Analysis
英文摘要: Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate forecasts lead to ineffective prioritization of conservation activities and potentially to avoidable species extinctions. © 2014 John Wiley & Sons Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62158
Appears in Collections: 影响、适应和脆弱性
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作者单位: The Centre of Excellence for Environmental Decisions, School of Botany, University of Melbourne, Parkville, Melbourne, Vic., 3010, Australia; CSIRO Ecosystem Sciences, Berrimah 0828, Darwin, NT, Australia; Department of Land Resource Management, Berrimah 0828, Darwin, NT, Australia
Recommended Citation:
Crase B.,Liedloff A.,Vesk P.A.,et al. Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts[J]. Global Change Biology,2014-01-01,20(8)